Facial mimicry and metacognitive judgments in emotion recognition are distinctly modulated by social anxiety and autistic traits

Facial mimicry as well as the accurate assessment of one's performance when judging others’ emotional expressions have been suggested to inform successful emotion recognition. Differences in the integration of these two information sources might explain alterations in the perception of others’ emotions in individuals with Social Anxiety Disorder and individuals on the autism spectrum. Using a non-clinical sample (N = 57), we examined the role of social anxiety and autistic traits in the link between facial mimicry, or confidence in one’s performance, and emotion recognition. While participants were presented with videos of spontaneous emotional facial expressions, we measured their facial muscle activity, asked them to label the expressions and indicate their confidence in accurately labelling the expressions. Our results showed that confidence in emotion recognition was lower with higher social anxiety traits even though actual recognition was not related to social anxiety traits. Higher autistic traits, in contrast, were associated with worse recognition, and a weakened link between facial mimicry and performance. Consequently, high social anxiety traits might not affect emotion recognition itself, but the top-down evaluation of own abilities in emotion recognition contexts. High autistic traits, in contrast, may be related to lower integration of sensorimotor simulations, which promote emotion recognition.


Distribution of the clinical trait score variables
Descriptive tables Table S0. Descriptive statistics of the accuracies and relative accuracies (scaled) by emotion category (N = 57 subjects).

Accuracy
Relative Accuracy (  Observations 3124 Marginal R 2 / Conditional R 2 0.521 / 0.600 † taken from general linear hypothesis calculation, z-score instead of t-value   Model fits with relative emotion recognition accuracy (additional analysis) Observations 3360 Marginal R 2 / Conditional R 2 0.443 / 0.513 † taken from general linear hypothesis calculation, z-score instead of t-value Table S24. Results of the linear mixed-effects model predicting relative recognition accuracy of angry facial expressions by social anxiety trait, corrugator muscle activity and the 2-way interaction between social anxiety traits and corrugator muscle activity Marginal R 2 / Conditional R 2 0.009 / 0.509 Table S25. Results of the linear mixed-effects model predicting relative recognition accuracy of happy facial expressions by social anxiety traits, zygomaticus muscle activity, corrugator muscle activity and the 2-way interactions between social anxiety traits and each muscles activity Marginal R 2 / Conditional R 2 0.012 / 0.481 Table S26. Results of the linear mixed-effects model predicting relative recognition accuracy of fearful facial expressions by social anxiety traits, corrugator muscle activity and the 2-way interaction between social anxiety traits and corrugator muscle activity Marginal R 2 / Conditional R 2 0.003 / 0.417 Table S27. Results of the linear mixed-effects model predicting relative recognition accuracy of sad facial expressions by social anxiety traits, corrugator muscle activity and the 2-way interaction between social anxiety traits and corrugator muscle activity

Data analysis
In order to explore whether social anxiety traits were associated with alterations in how emotionally intense the expressions were perceived, we calculated a LMM on perceived emotional intensity with emotion category, the trait dimension and their interaction as predictors. The identity of the stimulus and the participant ID were both added as random effects (random intercept), thus mirroring the other behavioural models. Coefficients for the emotion categories (main effects and interactions) were calculated by contrasting the respective category against the overall effect. For the neutral category, coefficients were calculated and tested (z-tests) using general hypotheses testing.

Results
Descriptive statistics. The six emotion categories also varied in how emotionally intense they  and social anxiety traits. Thus, in line with the accuracy results, we did not find support for a heightened sensitivity to specifically negative facial expressions with higher social anxiety traits in the perceived emotional intensity ratings (see Fig. S3(A) and Table S32).
Taken together, the relationship between autistic traits and perceived emotional intensity seems to depend on the displayed expression.

Short discussion
Interestingly, the expressions' perceived emotional intensity ratings mirrored the overall pattern of the confidence ratings (see Results section in manuscript), with happy, surprised and neutral expressions receiving ratings above, and angry, fearful and sad receiving ratings below the average. This overlap might be explained by differences in facial expressiveness between the stimuli which was shown to influence both estimated readability and actual readability of expressions (Alkhaldi et al., unpublished results). Hence, less expressive displays might have been rated as both less intense and more difficult to classify (lower confidence). Observations 3420

Model fits
Marginal R 2 / Conditional R 2 0.122 / 0.331 † taken from general linear hypothesis calculation, z-score instead of t-value